GLUCOSE SENSOR SIGNAL PURITY ANALYSIS

• US 20140128706A1
• Filed: 01/14/2014
• Published: 05/08/2014
• Est. Priority Date: 10/28/2010
• Status: Abandoned Application

• Current Assignee: Medtronic Minimed Incorporated (Medtronic Plc)
• Original Assignee: Medtronic Minimed Incorporated (Medtronic Plc)
• Inventors: Roy, Anirban
• Application Number:
  US14/154,852
• Publication Number:
  US 20140128706A1
• Time in Patent Office: Days
• US Class Current: 600/365
• CPC Class Codes: A61B 5/14532 for measuring glucose, e.g. by tissue impedance measurement
• CPC Class Codes: A61B 5/14865 invasive, e.g. introduced into the body by a catheter or needle or using implanted sensors
• CPC Class Codes: A61B 5/4839 combined with drug delivery
• CPC Class Codes: A61B 5/6849 in combination with a needle set
• CPC Class Codes: A61B 5/7203 for noise prevention, reduction or removal
• CPC Class Codes: A61B 5/7221 Determining signal validity, reliability or quality A61B5/7207 and A61B5/7217 take precedence
• CPC Class Codes: A61M 5/1723 using feedback of body parameters, e.g. blood-sugar, pressure measurement of body parameters A61B5/00
• CPC Class Codes: G01N 33/48 Biological material, e.g. blood, urine G01N33/02, G01N33/26, G01N33/44, G01N33/46 take precedence; Haemocytometers counting blood corpuscules distributed over a surface by scanning the surface G06M11/02

Abstract

Disclosed are methods, apparatuses, etc. for glucose sensor signal purity analysis. In certain example embodiments, a series of samples of at least one sensor signal that is responsive to a blood glucose level of a patient may be obtained. Based at least partly on the series of samples, at least one metric may be determined to characterize one or more non-physiological anomalies of a representation of the blood glucose level of the patient by the at least one sensor signal. A reliability of the at least one sensor signal to represent the blood glucose level of the patient may be assessed based at least partly on the at least one metric. Other example embodiments are disclosed herein.

Claims

1. A method comprising:

obtaining a series of samples of at least one sensor signal that is responsive to a blood glucose level of a patient;

determining, via a controller and based at least partly on the series of samples, at least one metric to characterize one or more non-physiological anomalies of a representation of the blood glucose level of the patient by the at least one sensor signal, wherein the one or more non-physiological anomalies comprise artificial dynamics of the at least one sensor signal that do not correlate with blood glucose levels of the patient; and

assessing a reliability of the at least one sensor signal to represent the blood glucose level of the patient based at least partly on the at least one metric.

2. The method of claim 1, further comprising:

generating an alert signal responsive to a comparison of the at least one metric with at least one predetermined threshold.

3. The method of claim 2, wherein said generating an alert comprises:

initiating a signal to indicate to a blood glucose controller that a sensor that generated the at least one sensor signal was not functioning reliably for at least part of a time while the series of samples was being obtained.

4. The method of claim 2, wherein said generating an alert comprises:

presenting at least one human-perceptible indication that a sensor that generated the at least one sensor signal was not functioning reliably for at least part of a time while the series of samples was being obtained.

5. The method of claim 1, further comprising:

acquiring the at least one sensor signal from one or more subcutaneous glucose sensors, wherein the at least one metric reflects an apparent reliability of the at least one sensor signal that is acquired from the one or more subcutaneous glucose sensors.

6. The method of claim 1, wherein the at least one metric quantitatively represents a deviation between the blood glucose level of the patient and the at least one sensor signal.

7. The method of claim 6, wherein the at least one metric reflects a noise level of the at least one sensor signal and/or an artifact level of the at least one sensor signal.

8. The method of claim 1, further comprising:

altering an insulin infusion treatment for the patient responsive at least partly to the assessed reliability of the at least one sensor signal.

9. The method of claim 1, wherein said determining at least one metric comprises:

ascertaining a residual portion of the at least one sensor signal based at least in part on the series of samples of the at least one sensor signal, said at least one sensor signal comprising one or more principle components and said residual portion; and

determining at least one value associated with the residual portion of the at least one sensor signal.

10. The method of claim 9, further comprising:

ascertaining said one or more principal components of the at least one sensor signal based at least in part on the series of samples of the at least one sensor signal,

wherein;

said ascertaining a residual portion further comprises ascertaining the residual portion of the at least one sensor signal based at least in part on the ascertained one or more principal components; and

said determining at least one value associated with the residual portion further comprises estimating a characteristic of random noise expressed in a subspace associated with the residual portion of the at least one sensor signal, the characteristic comprising one or more values descriptive of how data are distributed with respect to an average of the data.

11. The method of claim 1, wherein a characterization of the one or more non-physiological anomalies comprises detection of the artificial dynamics of the at least one sensor signal using the series of samples of the at least one sensor signal.

12. An apparatus comprising:

a controller to obtain a series of samples of at least one sensor signal that is responsive to a blood glucose level of a patient, said controller comprising one or more processors to;

determine, based at least partly on the series of samples, at least one metric to characterize one or more non-physiological anomalies of a representation of the blood glucose level of the patient by the at least one sensor signal, wherein the one or more non-physiological anomalies comprise artificial dynamics of the at least one sensor signal that do not correlate with blood glucose levels of the patient; and

assess a reliability of the at least one sensor signal to represent the blood glucose level of the patient based at least partly on the at least one metric.

13. The apparatus of claim 12, wherein said one or more processors of said controller are further to:

generate an alert signal responsive to a comparison of the at least one metric with at least one predetermined threshold.

14. The apparatus of claim 13, wherein said controller is capable of generating an alert by:

initiating a signal to indicate to a blood glucose controller that a sensor that generated the at least one sensor signal was not functioning reliably for at least part of a time while the series of samples was being obtained.

15. The apparatus of claim 13, wherein said controller is capable of generating an alert by:

presenting at least one human-perceptible indication that a sensor that generated the at least one sensor signal was not functioning reliably for at least part of a time while the series of samples was being obtained.

16. The apparatus of claim 12, wherein said one or more processors of said controller are further to:

acquire the at least one sensor signal from one or more subcutaneous glucose sensors, wherein the at least one metric reflects an apparent reliability of the at least one sensor signal that is acquired from the one or more subcutaneous glucose sensors.

17. The apparatus of claim 12, wherein the at least one metric quantitatively represents a deviation between the blood glucose level of the patient and the at least one sensor signal.

18. The apparatus of claim 17, wherein the at least one metric reflects a noise level of the at least one sensor signal and/or an artifact level of the at least one sensor signal.

19. The apparatus of claim 12, wherein said one or more processors of said controller are further to:

alter an insulin infusion treatment for the patient responsive at least partly to the assessed reliability of the at least one sensor signal.

20. The apparatus of claim 12, wherein said controller is capable of determining at least one metric by:

ascertaining a residual portion of the at least one sensor signal based at least in part on the series of samples of the at least one sensor signal, said at least one sensor signal comprising one or more principle components and said residual portion; and

determining at least one value associated with the residual portion of the at least one sensor signal.

21. The apparatus of claim 20, wherein said one or more processors of said controller are further to:

ascertain said one or more principal components of the at least one sensor signal based at least in part on the series of samples of the at least one sensor signal,

wherein;

said controller is capable of ascertaining a residual portion by ascertaining the residual portion of the at least one sensor signal based at least in part on the ascertained one or more principal components; and

said controller is capable of determining at least one value associated with the residual portion by estimating a characteristic of random noise expressed in a subspace associated with the residual portion of the at least one sensor signal, the characteristic comprising one or more values descriptive of how data are distributed with respect to an average of the data.

22. The apparatus of claim 12, wherein a characterization of the one or more non-physiological anomalies comprises detection of the artificial dynamics of the at least one sensor signal using the series of samples of the at least one sensor signal.

23. A system comprising:

means for obtaining a series of samples of at least one sensor signal that is responsive to a blood glucose level of a patient;

means for determining, based at least partly on the series of samples, at least one metric to characterize one or more non-physiological anomalies of a representation of the blood glucose level of the patient by the at least one sensor signal, wherein the one or more non-physiological anomalies comprise artificial dynamics of the at least one sensor signal that do not correlate with blood glucose levels of the patient; and

means for assessing a reliability of the at least one sensor signal to represent the blood glucose level of the patient based at least partly on the at least one metric.

24. An article comprising:

at least one storage medium having stored thereon instructions executable by one or more processors to;

obtain a series of samples of at least one sensor signal that is responsive to a blood glucose level of a patient;

determine, based at least partly on the series of samples, at least one metric to characterize one or more non-physiological anomalies of a representation of the blood glucose level of the patient by the at least one sensor signal, wherein the one or more non-physiological anomalies comprise artificial dynamics of the at least one sensor signal that do not correlate with blood glucose levels of the patient; and

assess a reliability of the at least one sensor signal to represent the blood glucose level of the patient based at least partly on the at least one metric.